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How to use as_complex method in autotest

Best Python code snippet using autotest_python

curvelet.py

Source:curvelet.py

1import numpy as np2# -----------------------------------------------------------------------------3#                             FUNCTION API4# -----------------------------------------------------------------------------5def curvelet_transform(x, num_bands, num_angles = 8, all_curvelets = True, as_complex = False):6    ndims = len(x.shape)7    # This file requires Curvelab and the PyCurveLab packages be installed on your system.8    try:9        import pyct10    except ImportError:11        raise NotImplementedError("Use of curvelets requires installation of CurveLab and the PyCurveLab package.\nSee: http://curvelet.org/  and  https://www.slim.eos.ubc.ca/SoftwareLicensed/")12    if ndims == 2:13        ct = pyct.fdct2( n = x.shape,14                         nbs = num_bands,   # Number of bands15                         nba = num_angles,  # Number of discrete angles16                         ac = all_curvelets,# Return curvelets at the finest detail level17                         vec = False,       # Return results as nested python vectors18                         cpx = as_complex)  # Disable complex-valued curvelets19    elif ndims == 3:20        ct = pyct.fdct3( n = x.shape,21                         nbs = num_bands,   # Number of bands22                         nba = num_angles,  # Number of discrete angles23                         ac = all_curvelets,# Return curvelets at the finest detail level24                         vec = False,       # Return results as nested python vectors25                         cpx = as_complex)  # Disable complex-valued curvelets26    else:27        raise NotImplementedError("%dD Curvelets are not supported." % (ndims))28    result = ct.fwd(x)29    del ct30    return result31def inverse_curvelet_transform(coefs, x_shape, num_bands, num_angles, all_curvelets, as_complex):32    # This file requires Curvelab and the PyCurveLab packages be installed on your system.33    try:34        import pyct35    except ImportError:36        raise NotImplementedError("Use of curvelets requires installation of CurveLab and the PyCurveLab package.\nSee: http://curvelet.org/  and  https://www.slim.eos.ubc.ca/SoftwareLicensed/")37    if len(x_shape) == 2:38        ct = pyct.fdct2( n = x_shape,39                          nbs = num_bands,     # Number of bands40                          nba = num_angles,41                          ac = all_curvelets,42                          vec = False,43                          cpx = as_complex)44    else:45        ct = pyct.fdct3( n = x_shape,46                          nbs = num_bands,     # Number of bands47                          nba = num_angles,48                          ac = all_curvelets,49                          vec = False,50                          cpx = as_complex)51    result = ct.inv(coefs)52    del ct53    return result54# -----------------------------------------------------------------------------55#                         OBJECT-ORIENTED API56# -----------------------------------------------------------------------------57class CurveletTransform(object):58    def __init__(self, x_shape, num_bands = None, num_angles = 8, all_curvelets = True, as_complex = False):59        if num_bands == None:60            self._num_bands = int(np.ceil(np.log2(np.min(x_shape)) - 3))61        else:62            self._num_bands = num_bands63        self.x_shape = x_shape64        self.num_angles = num_angles65        self.all_curvelets = all_curvelets66        self.as_complex = as_complex67        self.example_coefs = self.fwd(np.zeros(x_shape))68    # ------------- Forward and inverse transforms ------------------69    def fwd(self, data, num_bands = None):70        '''71        Curvelets must have the num_bands initialized in the72        constructor, but for uniformity with the API for forward73        transforms, we allow the user to supply a num_bands74        argument.  If the supplied num_bands does not match the75        num_bands used in the constructor, an error is generated.76        '''77        if num_bands != None:78            assert self._num_bands == num_bands79        # Check argument80        assert data.shape == self.x_shape81        ndims = len(self.x_shape)82        if ndims == 1:83            raise NotImplementedError("1D curvelet transform not yet implemented.")84        elif ndims == 2:85            return curvelet_transform(data, self._num_bands, self.num_angles, self.all_curvelets, self.as_complex)86        elif ndims == 3:87            return curvelet_transform(data, self._num_bands, self.num_angles, self.all_curvelets, self.as_complex)88        else:89            raise NotImplementedError("Curveletes not supported for %dD data." % (len(data.shape)))90    def inv(self, coefs):91        ndims = len(self.x_shape)92        if ndims == 1:93            raise NotImplementedError("1D Inverse curvelet transform not yet implemented.")94        elif ndims == 2:95            return inverse_curvelet_transform(coefs, self.x_shape, self._num_bands, self.num_angles,96                                              self.all_curvelets, self.as_complex)97        elif ndims == 3:98            return inverse_curvelet_transform(coefs, self.x_shape, self._num_bands, self.num_angles,99                                              self.all_curvelets, self.as_complex)100        else:101            raise NotImplementedError("Curvelets not supported for %dD data." % (len(data.shape)))102    # --------------------- Utility methods -------------------------103    def num_bands(self, coefs):104        return self._num_bands105    def num_coefficients(self):106        total = 0107        for band in self.example_coefs:108            total += sum([ np.prod(angle.shape) for angle in band ] )109        return total110    def num_nonzero_coefficients(self, coefs):111        total = 0112        for band in coefs:113            total += sum([ angle.nonzero()[0].shape[0] for angle in band ] )114        return total115    def coefs_to_vec(self, coefs):116        return np.hstack([np.hstack([ angle.ravel(order = 'c') for angle in band ]) for band in coefs])117    def vec_to_coefs(self, coef_vec):118        base_idx = 0119        coefs = []120        for band in self.example_coefs:121            angle_list = []122            for angle in band:123                angle_size = np.prod(angle.shape)124                angle_list.append(np.reshape(coef_vec[base_idx:base_idx+angle_size], angle.shape, order = 'c'))125                base_idx += angle_size126            coefs.append(angle_list)127        return coefs128    def update(self, coefs, update, alpha):129        '''130        Adds the update (multiplied by alpha) to each set of131        coefficients.132        '''133        delta_sqrsum = 0.0134        for band in xrange(len(coefs)):135            for angle in xrange(len(coefs[band])):136                delta = alpha * update[band][angle]137                coefs[band][angle] += delta138                delta_sqrsum += np.square(delta).sum()139        update_norm = np.sqrt(delta_sqrsum)140        return (coefs, update_norm)141    def mean(self, coefs):142        '''143        Compute the average over all wavelet coefficients.144        '''145        accum = []146        for coef in coefs:147            accum.append(np.hstack( [ block.ravel() for block in coef ] ))148        return np.hstack(accum).mean()149    # ------------------ Thresholding methods -----------------------150    def _estimate_noise(self):151        '''152        Helper function for the thresholding function below.153        Adapted from the fdct_osfft_demo_denoise.m file in CurveLab.154        '''155        E_coefs = self.fwd(np.random.randn(*self.x_shape))156        E_thresholds = []157        for band in xrange(len(E_coefs)):158            angle_thresholds = []159            for angle in xrange(len(E_coefs[band])):160                A = E_coefs[band][angle]161                angle_thresholds.append( np.median(np.abs(A - np.median(A)))/0.6745 )162            E_thresholds.append(angle_thresholds)163        return E_thresholds164    def threshold_by_band(self, coefs, threshold_func, skip_bands = [], within_axis = None, scaling_factor = None):165        '''166        Threshold each band individually.  The threshold_func() should167        take an array of coefficients (which may be 1d or 2d or 3d),168        and return a tuple: (band_center, band_threshold)169        For the sake of speed and memory efficiency, updates to the coefficients170        are performed in-place.171        '''172        # Skip the lowest frequency band173        for b in xrange(1, len(coefs)):174            num_removed = 0175            num_total = 0176            # Skip band?177            if b in skip_bands:178                continue179            # print num_total - num_removed, num_total180            # Compute the center and threshold.181            tmp = np.hstack( [ angle.ravel() for angle in coefs[b] ] )182            (band_center, band_threshold) = threshold_func(tmp, b, None)183            # print '\t\t****', b, band_center, band_threshold184            #if scaling_factor != None:185            #    band_threshold /= scaling_factor186            for a in xrange(len(coefs[b])):187                # Soft threshold the coefficients188                idxs = np.where( coefs[b][a] > band_threshold )189                coefs[b][a][idxs] -= band_threshold190                idxs = np.where( np.abs(coefs[b][a]) <= band_threshold )191                coefs[b][a][idxs] = 0.0192                idxs = np.where( coefs[b][a] < -band_threshold )193                coefs[b][a][idxs] += band_threshold194                #idxs = np.where( np.abs( coefs[b][a] - band_center ) < band_threshold )#  * scaling_factor[b][a] / max_scale )195                #num_removed += idxs[0].shape[0]196                #num_total += np.prod(coefs[b][a].shape)197                #coefs[b][a][idxs] = 0.0198            #print 'Retained %0.2f -- ( %g / %g )' % (100.0*(num_total - num_removed)/float(num_total),199            #                                         num_total - num_removed, num_total)...

test_api.py

Source:test_api.py

1#!/usr/bin/env python2# -*- coding: utf-8 -*-3#4# parselglossy -- Generic input parsing library, speaking in tongues5# Copyright (C) 2020 Roberto Di Remigio, Radovan Bast, and contributors.6#7# This file is part of parselglossy.8#9# Permission is hereby granted, free of charge, to any person obtaining a copy10# of this software and associated documentation files (the "Software"), to deal11# in the Software without restriction, including without limitation the rights12# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell13# copies of the Software, and to permit persons to whom the Software is14# furnished to do so, subject to the following conditions:15#16# The above copyright notice and this permission notice shall be included in17# all copies or substantial portions of the Software.18#19# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR20# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,21# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE22# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER23# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,24# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE25# SOFTWARE.26#27# For information on the complete list of contributors to the28# parselglossy library, see: <http://parselglossy.readthedocs.io/>29#30"""Tests for `parselglossy` package."""31import json32from pathlib import Path33from shutil import rmtree34import pytest35from parselglossy import api36from parselglossy.utils import as_complex37@pytest.mark.parametrize(38    "args,out,reference",39    [40        (("tests/api/standard.inp",), None, "tests/ref/standard_ir.json"),41        (42            ("tests/api/scf.inp", "standard", "scf_ir.json"),43            "scf_ir.json",44            "tests/ref/scf_ir.json",45        ),46        (47            ("tests/api/getkw.inp", "getkw", "lex_ir.json"),48            "lex_ir.json",49            "tests/ref/getkw_ir.json",50        ),51    ],52    ids=["lex-default", "lex-standard-w-outfile", "lex-getkw-w-outfile"],53)54def test_api_lex(args, out, reference):55    ir = api.lex(*args)56    # Check intermediate representation matches with reference57    ref_json = Path(reference).resolve()58    if out is None:59        with ref_json.open("r") as f:60            assert ir == json.loads(f.read(), object_hook=as_complex)61    else:62        dumped = Path(out).resolve()63        with ref_json.open("r") as ref, dumped.open("r") as o:64            assert json.loads(o.read(), object_hook=as_complex) == json.loads(65                ref.read(), object_hook=as_complex66            )67        # Clean up JSON file68        dumped.unlink()69@pytest.mark.parametrize(70    "args,out,reference",71    [72        (73            ("tests/ref/scf_ir.json", "tests/validation/overall/template.yml"),74            None,75            "tests/ref/scf_fr.json",76        ),77        (78            (79                "tests/ref/scf_ir.json",80                "tests/validation/overall/template.yml",81                "scf_fr.json",82            ),83            "scf_fr.json",84            "tests/ref/scf_fr.json",85        ),86    ],87    ids=["validate-default", "validate-w-outfile"],88)89def test_api_validate(args, out, reference):90    fr = api.validate(*args)91    # Check final representation matches with reference92    ref_json = Path(reference).resolve()93    if out is None:94        with ref_json.open("r") as f:95            assert fr == json.loads(f.read(), object_hook=as_complex)96    else:97        dumped = Path(out).resolve()98        with ref_json.open("r") as ref, dumped.open("r") as o:99            assert json.loads(o.read(), object_hook=as_complex) == json.loads(100                ref.read(), object_hook=as_complex101            )102        # Clean up JSON file103        dumped.unlink()104@pytest.mark.parametrize(105    "args,out,reference",106    [107        (108            ("tests/api/scf.inp", "tests/validation/overall/template.yml"),109            None,110            "tests/ref/scf_fr.json",111        ),112        (113            (114                "tests/api/scf.inp",115                "tests/validation/overall/template.yml",116                "scf_fr.json",117            ),118            "scf_fr.json",119            "tests/ref/scf_fr.json",120        ),121        (122            (123                "tests/api/scf.inp",124                "tests/validation/overall/template.yml",125                None,126                "standard",127                True,128            ),129            None,130            "tests/ref/scf_fr.json",131        ),132    ],133    ids=["parse-default", "parse-w-outfile", "parse-w-dumpir"],134)135def test_api_parse(args, out, reference):136    fr = api.parse(*args)137    # Check final representation matches with reference138    ref_json = Path(reference).resolve()139    if out is None:140        with ref_json.open("r") as f:141            assert fr == json.loads(f.read(), object_hook=as_complex)142    else:143        dumped = Path(out).resolve()144        with ref_json.open("r") as ref, dumped.open("r") as o:145            assert json.loads(o.read(), object_hook=as_complex) == json.loads(146                ref.read(), object_hook=as_complex147            )148        # Clean up JSON file149        dumped.unlink()150@pytest.mark.parametrize(151    "args,out,reference",152    [153        (("tests/api/docs_template.yml",), None, "tests/ref/input.rst"),154        (155            ("tests/api/docs_template.yml", "input.rst"),156            "input.rst",157            "tests/ref/input.rst",158        ),159        (160            (161                "tests/api/docs_template.yml",162                "input.rst",163                "Dwigt Rortugal's guide to input parameters",164            ),165            "input.rst",166            "tests/ref/dwigt.rst",167        ),168    ],169    ids=["document-default", "document-w-outfile", "document-w-header"],170)171def test_api_document(args, out, reference):172    docs = api.document(*args)173    # Check final representation matches with reference174    ref_rst = Path(reference).resolve()175    if out is None:176        with ref_rst.open("r") as ref:177            assert docs == ref.read()178    else:179        dumped = Path(out).resolve()180        with ref_rst.open("r") as ref, dumped.open("r") as o:181            assert o.read() == ref.read()182        # Clean up .rst file183        dumped.unlink()184@pytest.mark.parametrize(185    "args,inp,references",186    [187        (188            {189                "template": "tests/validation/overall/template.yml",190                "docfile": "foo.rst",191                "grammar": "standard",192            },193            "tests/api/scf.inp",194            ("tests/ref/scf_fr.json", "tests/ref/generated_input.rst"),195        ),196        (197            {198                "template": "tests/validation/overall/template.yml",199                "docfile": "babar.rst",200                "grammar": [201                    Path(__file__).parents[1].absolute()202                    / f"parselglossy/grammars/{x}.py"203                    for x in ["atoms", "getkw"]204                ],205                "tokenize": "from . import getkw; lexer = getkw.grammar(has_complex=True); ir = lexer.parseString(in_str).asDict()",206            },207            "tests/api/scf.inp",208            ("tests/ref/scf_fr.json", "tests/ref/generated_input.rst"),209        ),210    ],211    ids=["generate-default", "generated-custom-grammar"],212)213def test_api_generate(args, inp, references):214    # generate parser215    parser_dir = api.generate(**args)216    # use generated parser to parse inp217    from input_parser import api as generated_api218    fr = generated_api.parse(inp)219    # Check final representation matches with reference220    ref_json = Path(references[0]).resolve()221    with ref_json.open("r") as ref:222        assert fr == json.loads(ref.read(), object_hook=as_complex)223    # Check generated documentation agrees with reference224    ref_rst = Path(references[1]).resolve()225    dumped = parser_dir / f"docs/{args['docfile']}"226    with ref_rst.open("r") as ref, dumped.open("r") as o:227        assert o.read() == ref.read()228    # clean up generated parser...

conversions.py

Source:conversions.py

1def int_to_str(value, width):2    """3    Outputs a string of the binary of the value with4    LSB to the left.5    """6    s = bin(value)[2:]7    assert len(s) <= width8    s = '0' * (width - len(s)) + s9    return s10def signed_to_slv(value, width):11    """12    Takes a value between -1 to 1 inclusive and maps it13    into `width` bits.14    >>> bin(signed_to_slv(1, 8))15    '0b1000000'16    >>> bin(signed_to_slv(-1, 8))17    '0b11000000'18    """19    assert abs(value) <= 120    max_mag = pow(2, width-2)21    scaled = round(value * max_mag)22    if scaled < 0:23        scaled = pow(2, width) + scaled24    assert scaled < pow(2, width)25    assert isinstance(scaled, int)26    return scaled27def slv_to_signed(value, width):28    max_mag = pow(2, width-2)29    if value >= pow(2, width-1):30        value = value - pow(2, width)31    scaled = value / max_mag32    assert scaled <= 133    return scaled34def complex_to_slv(value, width):35    """36    Maps a complex number, `value`, (with mag <= 1) to an integer with37    bit width of width `width`.38    >>> bin(complex_to_slv(1+0j, 12))39    '0b10000000000'40    >>> bin(complex_to_slv(0.5-0.5j, 12))41    '0b1000111000'42    """43    assert width % 2 == 044    assert abs(value) <= 145    mapped_real = signed_to_slv(value.real, width//2)46    mapped_imag = signed_to_slv(value.imag, width//2)47    mapped = mapped_imag + mapped_real * pow(2, width//2)48    return mapped49def complex_from_slv(value, width):50    """51    Maps an integer (with bit-width `width`)52    to a complex number.53    """54    assert value < pow(2, width)55    assert width % 2 == 056    real_part = value >> width//257    imag_part = value % pow(2, width//2)58    imag_float = slv_to_signed(imag_part, width//2)59    real_float = slv_to_signed(real_part, width//2)60    as_complex = real_float + imag_float * (0+1j)61    return as_complex62def list_of_complex_to_slv(values, width):63    slv = 064    f = 165    for value in values:66        slv += complex_to_slv(value, width) * f67        f = f << width68    return slv69def list_of_complex_from_slv(value, width, size):70    assert value < pow(2, width*size)71    bits = ''.join(reversed(bin(value)[2:]))72    assert len(bits) <= width * size73    bits += '0' * (width*size - len(bits))74    lumps = [bits[index*width: (index+1)*width]75             for index in range(size)]76    complexes = []77    for lump in lumps:78        as_int = int(''.join(reversed(lump)), 2)79        as_complex = complex_from_slv(as_int, width)80        complexes.append(as_complex)81    return complexes82def list_of_uints_to_slv(values, width):83    slv = 084    f = 185    step = pow(2, width)86    for value in values:87        slv += value * f88        f *= step89    return slv90def list_of_uints_from_slv(slv, width, size):91    step = pow(2, width)92    values = []93    for i in range(size):94        values.append(slv % step)95        slv = slv >> width96    assert slv == 097    return values98if __name__ == '__main__':99    import doctest...

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